Digital Health Interventions to Improve Cardiometabolic Risk Profile among Adults with Obesity and Chronic Diseases: A Systematic Review

Abstract

Digital Health Interventions to Improve Cardiometabolic Risk Profile among Adults with Obesity and Chronic Diseases: A Systematic Review Hoirun Nisa1, Fadi Barsbay2 1Faculty of Health Sciences, Syarif Hidayatullah State Islamic University (UIN), Jakarta, Indonesia 2The University of New Orleans, New Orleans, USA Article Info Abstract Article History: Received: 2 September 2021 Revised: 23 March 2022 Accepted: 29 March 2022 Online: 27 April 2022 Keywords: Adults, cardiometabolic risk, chronic disease, digital health Corresponding Author: Hoirun Nisa Department of Public Health, Faculty of Health Sciences Syarif Hidayatullah State Islamic University (UIN) Jakarta, Indonesia. Email: hoirun.nisa@uinjkt.ac.id Background: The prevalence of chronic diseases is rapidly increasing globally. Ubiquitous digital technologies give an opportunity for digital health intervention to improve cardiometabolic risk (CMR) profile that may consequently decrease the risk of chronic diseases. However, evidence on digital health associated with chronic disease interventions remains controversial. Purpose: This systematic review aimed to determine the association of digital health intervention with improving CMR profile of adults with obesity and chronic diseases. Methods: A comprehensive search of Medline, CINAHL, Embase, and PubMed was performed using the following criteria: publication between 2016-2021, using digital health tools as interventions, adults with obesity or chronic diseases, cardiometabolic profile as outcomes, and randomized controlled trial (RCT) as the design. The search yielded 548 articles of which 13 studies met the inclusion criteria. The Joanna Briggs checklist for RCT was used to assess the quality of the studies. Data analysis was conducted according to the guidance for synthesis without meta-analysis. Results: There were 8 (61.5%) out of 13 studies assessed the relationship between digital health interventions and weight, of which 7 studies (88%) found positive findings. The association between digital health intervention and blood pressure were assessed in 7 (53.8%) out 13 studies, of which only two studies had positive findings related with systolic blood pressure. The intervention modalities included m-Health (apps) in 2 studies, text-messaging in 4 studies, and combinations of modalities in 8 studies. The interventions used different strategies, including education, self-management, and social support. More than a half of the studies (54%) were about weight-loss interventions and 10 (76.9%) studies used education for intervention components. Conclusions: Digital health intervention may be associated with decreased weight and BMI; however, only a few studies assessed other CMR profile, and the findings were inconsistent. Additional studies are needed to assess digital health interventions targeting other CMR profile, including blood pressure, glucose, and cholesterol level.